Models Predicting Hospital Admission of Adult Patients Utilizing Prehospital Data: Systematic Review Using PROBAST and CHARMS.
Ann Corneille MonahanSue S FeldmanPublished in: JMIR medical informatics (2021)
There is incredible potential for prehospital admission prediction models to improve patient care and hospital operations. Patient data can be utilized to act as predictors and as data-driven, actionable tools to identify patients likely to require imminent hospital admission and reduce patient boarding and crowding in emergency departments. Prediction models can be used to justify earlier patient admission and care, to lower morbidity and mortality, and models that utilize biomarker predictors offer additional advantages.
Keyphrases
- emergency department
- systematic review
- healthcare
- case report
- cardiac arrest
- end stage renal disease
- adverse drug
- electronic health record
- acute care
- newly diagnosed
- ejection fraction
- big data
- randomized controlled trial
- chronic kidney disease
- peritoneal dialysis
- meta analyses
- patient reported outcomes
- climate change
- prognostic factors
- emergency medical
- human health
- affordable care act